Christopher C. Holmes

36 papers A* 6A 3C 1Journal 26
YearRankTypeTitle / Venue / Authors
2025 A conf
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation.
AISTATS
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Christopher C. Holmes, Yishai Shimoni
2025 A conf
Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition.
AISTATS
Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes
2025 A conf
On Subjective Uncertainty Quantification and Calibration in Natural Language Generation.
AISTATS
Ziyu Wang, Christopher C. Holmes
2024 J jnl
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection.
Trans. Mach. Learn. Res.
Sam Dauncey, Christopher C. Holmes, Christopher Williams, Fabian Falck
2024 J jnl
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers.
Nat. Mac. Intell.
Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes
2024 A* conf
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective.
ICML
Fabian Falck, Ziyu Wang, Christopher C. Holmes
2024 J jnl
Is merging worth it? Securely evaluating the information gain for causal dataset acquisition.
CoRR
Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes
2024 J jnl
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference.
CoRR
Oscar Clivio, Avi Feller, Christopher C. Holmes
2023 A* conf
PWSHAP: A Path-Wise Explanation Model for Targeted Variables.
ICML
Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes
2021 A* conf
Improving VAEs' Robustness to Adversarial Attack.
ICLR
Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes
2021 J jnl
Multi-Facet Clustering Variational Autoencoders.
CoRR
Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Christopher C. Holmes
2019 J jnl
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap.
CoRR
Edwin Fong, Simon Lyddon, Christopher C. Holmes
2019 J jnl
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels.
CoRR
Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes
2018 J jnl
Nonparametric learning from Bayesian models with randomized objective functions.
CoRR
Simon Lyddon, Stephen Walker, Christopher C. Holmes
2018 A* conf
Probabilistic Boolean Tensor Decomposition.
ICML
Tammo Rukat, Christopher C. Holmes, Christopher Yau
2018 J jnl
TensOrMachine: Probabilistic Boolean Tensor Decomposition.
CoRR
Tammo Rukat, Christopher C. Holmes, Christopher Yau
2017 A* conf
Bayesian Boolean Matrix Factorisation.
ICML
Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau
2017 J jnl
Bayesian Boolean Matrix Factorisation.
CoRR
Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau
2017 J jnl
On Markov chain Monte Carlo methods for tall data.
J. Mach. Learn. Res.
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
2014 A* conf
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach.
ICML
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
2013 J jnl
NucleoFinder: a statistical approach for the detection of nucleosome positions.
Bioinform.
Jérémie Becker, Christopher Yau, John M. Hancock, Christopher C. Holmes
2013 J jnl
Statistical Inference in Hidden Markov Models using $k$-segment Constraints.
CoRR
Michalis K. Titsias, Christopher Yau, Christopher C. Holmes
2012 J jnl
GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples.
Bioinform.
Jean-Baptiste Cazier, Christopher C. Holmes, John Broxholme
2011 J jnl
Stochastic boosting algorithms.
Stat. Comput.
Ajay Jasra, Christopher C. Holmes
2010 J jnl
A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.
Bioinform.
Taane G. Clark, Susana G. Campino, Elisa Anastasi, Sarah Auburn, Yik Y. Teo, Kerrin S. Small, Kirk A. Rockett, Dominic Kwiatkowski, Christopher C. Holmes
2009 J jnl
A boosting approach to structure learning of graphs with and without prior knowledge.
Bioinform.
Shahzia Anjum, Arnaud Doucet, Christopher C. Holmes
2009 J jnl
Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency.
Bioinform.
Jochen W. Klingelhoefer, Loukas Moutsianas, Christopher C. Holmes
2009 J jnl
Phylogenetic inference under recombination using Bayesian stochastic topology selection.
Bioinform.
Alex Webb, John M. Hancock, Christopher C. Holmes
2008 J jnl
GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population.
Bioinform.
Eleni Giannoulatou, Christopher Yau, Stefano Colella, Jiannis Ragoussis, Christopher C. Holmes
2008 J jnl
Interacting sequential Monte Carlo samplers for trans-dimensional simulation.
Comput. Stat. Data Anal.
Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes
2007 J jnl
On population-based simulation for static inference.
Stat. Comput.
Ajay Jasra, David A. Stephens, Christopher C. Holmes
2003 J jnl
Classification with Bayesian MARS.
Mach. Learn.
Christopher C. Holmes, Dave Denison
2001 C conf
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo.
ICANN
Stephen J. Roberts, Christopher C. Holmes, Dave Denison
2001 J jnl
Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo.
IEEE Trans. Pattern Anal. Mach. Intell.
Stephen J. Roberts, Christopher C. Holmes, Dave Denison
2000 J jnl
Bayesian wavelet networks for nonparametric regression.
IEEE Trans. Neural Networks Learn. Syst.
Christopher C. Holmes, Bani K. Mallick
1998 J jnl
Bayesian Radial Basis Functions of Variable Dimension.
Neural Comput.
Christopher C. Holmes, Bani K. Mallick